Python Evaluation from Chatbot 2025-07-29_17-34

Python Evaluation from Chatbot 2025-07-29_17-34 ID: OSW123e4567e89b12d3a456426614174000 | UUID: 123e4567-e89b-12d3-a456-426614174000
ID	OSW123e4567e89b12d3a456426614174000
UUID	123e4567-e89b-12d3-a456-426614174000
Label	Python Evaluation from Chatbot 2025-07-29_17-34
Machine compatible name	PythonEvaluationFromChatbot202507291734
Types/Categories	Python Evaluation Process
Statements (outgoing)
Statements (incoming)
Details
Types/Categories<br>Definition: Entity, Item, Process, Python Evaluation Process: Python Evaluation Process Label(s)At least one label is required.<br>Definition: Entity: Python Evaluation from Chatbot 2025-07-29_17-34 Outputs<br>Definition: Process: Plot from Chatbot 2025-07-29_17-34 python_evaluation_codethe python code of this evaluation<br>Definition: Python Evaluation Process: import matplotlib.pyplot as plt import networkx as nx Create a directed graph G = nx.DiGraph() Add nodes for inputs and outputs G.add_node("Input 1", color='lightblue') G.add_node("Input 2", color='lightblue') G.add_node("Process", color='lightgreen') G.add_node("Output 1", color='lightcoral') G.add_node("Output 2", color='lightcoral') Add edges to represent the process flow G.add_edges_from([ ("Input 1", "Process"), ("Input 2", "Process"), ("Process", "Output 1"), ("Process", "Output 2") ]) Define positions of nodes pos = { "Input 1": (-1, 1), "Input 2": (-1, -1), "Process": (0, 0), "Output 1": (1, 1), "Output 2": (1, -1) } Draw the graph plt.figure(figsize=(8, 6)) node_colors = [nx.get_node_attributes(G, "color")[node] for node in G.nodes()] nx.draw(G, pos, with_labels=True, node_size=3000, node_color=node_colors, font_size=10, font_weight='bold', arrowsize=20) plt.title("Process Flow Diagram") plt.savefig("/tmp/output.png") plt.show() Image<br>Definition: Entity: Plot from Chatbot 2025-07-29_17-34

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Item
Type(s)/Category(s)	Python Evaluation Process

Python-Code

import matplotlib.pyplot as plt
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add nodes for inputs and outputs
G.add_node("Input 1", color='lightblue')
G.add_node("Input 2", color='lightblue')
G.add_node("Process", color='lightgreen')
G.add_node("Output 1", color='lightcoral')
G.add_node("Output 2", color='lightcoral')

# Add edges to represent the process flow
G.add_edges_from([
    ("Input 1", "Process"),
    ("Input 2", "Process"),
    ("Process", "Output 1"),
    ("Process", "Output 2")
])

# Define positions of nodes
pos = {
    "Input 1": (-1, 1),
    "Input 2": (-1, -1),
    "Process": (0, 0),
    "Output 1": (1, 1),
    "Output 2": (1, -1)
}

# Draw the graph
plt.figure(figsize=(8, 6))
node_colors = [nx.get_node_attributes(G, "color")[node] for node in G.nodes()]

nx.draw(G, pos, with_labels=True, node_size=3000, node_color=node_colors, font_size=10, font_weight='bold', arrowsize=20)
plt.title("Process Flow Diagram")
plt.savefig("/tmp/output.png")
plt.show()

Process Graph

Graph

QR Code

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jsondata

uuid	"123e4567-e89b-12d3-a456-426614174000"
name	"PythonEvaluationFromChatbot202507291734"
label	text "Python Evaluation from Chatbot 2025-07-29_17-34" lang "en"
image	"File:OSW07ef97b871ee4cb78b4579f6e53c5d95.png"
meta	uuid "8067cdd8-d648-4abf-8b22-4e10de42489d" change_id "fcac22d6-a934-4968-8cac-b93be252767a"
type	"Category:OSW136953ec4cbf49ef80e2343c0e1981c0"
output	"File:OSW07ef97b871ee4cb78b4579f6e53c5d95.png"
python_evaluation_code	"import matplotlib.pyplot as plt import networkx as nx # Create a directed graph G = nx.DiGraph() # Add nodes for inputs and outputs G.add_node("Input 1", color='lightblue') G.add_node("Input 2", color='lightblue') G.add_node("Process", color='lightgreen') G.add_node("Output 1", color='lightcoral') G.add_node("Output 2", color='lightcoral') # Add edges to represent the process flow G.add_edges_from([ ("Input 1", "Process"), ("Input 2", "Process"), ("Process", "Output 1"), ("Process", "Output 2") ]) # Define positions of nodes pos = { "Input 1": (-1, 1), "Input 2": (-1, -1), "Process": (0, 0), "Output 1": (1, 1), "Output 2": (1, -1) } # Draw the graph plt.figure(figsize=(8, 6)) node_colors = [nx.get_node_attributes(G, "color")[node] for node in G.nodes()] nx.draw(G, pos, with_labels=True, node_size=3000, node_color=node_colors, font_size=10, font_weight='bold', arrowsize=20) plt.title("Process Flow Diagram") plt.savefig("/tmp/output.png") plt.show()"